Overview

Dataset statistics

Number of variables21
Number of observations47760
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.7 MiB
Average record size in memory168.0 B

Variable types

Numeric20
Categorical1

Alerts

lat is highly correlated with TMQ and 9 other fieldsHigh correlation
TMQ is highly correlated with lat and 10 other fieldsHigh correlation
U850 is highly correlated with UBOTHigh correlation
V850 is highly correlated with VBOTHigh correlation
UBOT is highly correlated with U850High correlation
VBOT is highly correlated with V850High correlation
QREFHT is highly correlated with lat and 9 other fieldsHigh correlation
PS is highly correlated with lat and 10 other fieldsHigh correlation
PSL is highly correlated with lat and 10 other fieldsHigh correlation
T200 is highly correlated with PS and 4 other fieldsHigh correlation
T500 is highly correlated with lat and 10 other fieldsHigh correlation
PRECT is highly correlated with TMQHigh correlation
TS is highly correlated with lat and 9 other fieldsHigh correlation
TREFHT is highly correlated with lat and 9 other fieldsHigh correlation
Z1000 is highly correlated with lat and 10 other fieldsHigh correlation
Z200 is highly correlated with lat and 10 other fieldsHigh correlation
ZBOT is highly correlated with lat and 9 other fieldsHigh correlation
lat is highly correlated with TMQ and 9 other fieldsHigh correlation
lon is highly correlated with T500 and 3 other fieldsHigh correlation
TMQ is highly correlated with lat and 9 other fieldsHigh correlation
U850 is highly correlated with UBOTHigh correlation
V850 is highly correlated with VBOTHigh correlation
UBOT is highly correlated with U850High correlation
VBOT is highly correlated with V850High correlation
QREFHT is highly correlated with lat and 9 other fieldsHigh correlation
PS is highly correlated with lat and 10 other fieldsHigh correlation
PSL is highly correlated with lat and 10 other fieldsHigh correlation
T200 is highly correlated with PS and 2 other fieldsHigh correlation
T500 is highly correlated with lat and 10 other fieldsHigh correlation
TS is highly correlated with lat and 10 other fieldsHigh correlation
TREFHT is highly correlated with lat and 10 other fieldsHigh correlation
Z1000 is highly correlated with lat and 10 other fieldsHigh correlation
Z200 is highly correlated with lat and 10 other fieldsHigh correlation
ZBOT is highly correlated with lat and 9 other fieldsHigh correlation
lat is highly correlated with QREFHT and 4 other fieldsHigh correlation
TMQ is highly correlated with QREFHT and 7 other fieldsHigh correlation
U850 is highly correlated with UBOTHigh correlation
V850 is highly correlated with VBOTHigh correlation
UBOT is highly correlated with U850High correlation
VBOT is highly correlated with V850High correlation
QREFHT is highly correlated with lat and 8 other fieldsHigh correlation
PS is highly correlated with TMQ and 4 other fieldsHigh correlation
PSL is highly correlated with TMQ and 4 other fieldsHigh correlation
T500 is highly correlated with QREFHT and 7 other fieldsHigh correlation
TS is highly correlated with lat and 6 other fieldsHigh correlation
TREFHT is highly correlated with lat and 6 other fieldsHigh correlation
Z1000 is highly correlated with TMQ and 3 other fieldsHigh correlation
Z200 is highly correlated with lat and 6 other fieldsHigh correlation
ZBOT is highly correlated with lat and 6 other fieldsHigh correlation
lat is highly correlated with lon and 11 other fieldsHigh correlation
lon is highly correlated with lat and 10 other fieldsHigh correlation
TMQ is highly correlated with lat and 16 other fieldsHigh correlation
U850 is highly correlated with TMQ and 8 other fieldsHigh correlation
V850 is highly correlated with TMQ and 8 other fieldsHigh correlation
UBOT is highly correlated with TMQ and 8 other fieldsHigh correlation
VBOT is highly correlated with TMQ and 5 other fieldsHigh correlation
QREFHT is highly correlated with lat and 11 other fieldsHigh correlation
PS is highly correlated with lat and 15 other fieldsHigh correlation
PSL is highly correlated with lat and 15 other fieldsHigh correlation
T200 is highly correlated with lat and 14 other fieldsHigh correlation
T500 is highly correlated with lat and 15 other fieldsHigh correlation
PRECT is highly correlated with TMQ and 5 other fieldsHigh correlation
TS is highly correlated with lat and 11 other fieldsHigh correlation
TREFHT is highly correlated with lat and 11 other fieldsHigh correlation
Z1000 is highly correlated with lat and 11 other fieldsHigh correlation
Z200 is highly correlated with lat and 9 other fieldsHigh correlation
ZBOT is highly correlated with lat and 11 other fieldsHigh correlation
LABELS is highly correlated with PS and 1 other fieldsHigh correlation
PRECT is highly skewed (γ1 = 35.72065413) Skewed
S.No is uniformly distributed Uniform
S.No has unique values Unique
PRECT has 1192 (2.5%) zeros Zeros

Reproduction

Analysis started2021-10-19 20:02:09.220780
Analysis finished2021-10-19 20:02:47.755661
Duration38.53 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

S.No
Real number (ℝ≥0)

UNIFORM
UNIQUE

Distinct47760
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23879.5
Minimum0
Maximum47759
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:47.816198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2387.95
Q111939.75
median23879.5
Q335819.25
95-th percentile45371.05
Maximum47759
Range47759
Interquartile range (IQR)23879.5

Descriptive statistics

Standard deviation13787.26877
Coefficient of variation (CV)0.5773684024
Kurtosis-1.2
Mean23879.5
Median Absolute Deviation (MAD)11940
Skewness0
Sum1140484920
Variance190088780
MonotonicityStrictly increasing
2021-10-19T16:02:47.904294image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01
 
< 0.1%
318431
 
< 0.1%
318341
 
< 0.1%
318351
 
< 0.1%
318361
 
< 0.1%
318371
 
< 0.1%
318381
 
< 0.1%
318391
 
< 0.1%
318401
 
< 0.1%
318411
 
< 0.1%
Other values (47750)47750
> 99.9%
ValueCountFrequency (%)
01
< 0.1%
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
ValueCountFrequency (%)
477591
< 0.1%
477581
< 0.1%
477571
< 0.1%
477561
< 0.1%
477551
< 0.1%
477541
< 0.1%
477531
< 0.1%
477521
< 0.1%
477511
< 0.1%
477501
< 0.1%

lat
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct24
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.933507171
Minimum-31.09517601
Maximum24.0547588
Zeros0
Zeros (%)0.0%
Negative23880
Negative (%)50.0%
Memory size373.2 KiB
2021-10-19T16:02:48.219567image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-31.09517601
5-th percentile-30.86049544
Q1-24.58279009
median-3.87222947
Q321.76662321
95-th percentile23.82007823
Maximum24.0547588
Range55.14993481
Interquartile range (IQR)46.3494133

Descriptive statistics

Standard deviation22.90675491
Coefficient of variation (CV)-7.80865823
Kurtosis-1.867271225
Mean-2.933507171
Median Absolute Deviation (MAD)23.23337679
Skewness0.009793084199
Sum-140104.3025
Variance524.7194207
MonotonicityNot monotonic
2021-10-19T16:02:48.285736image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
-24.758800521990
 
4.2%
23.820078231990
 
4.2%
-30.625814861990
 
4.2%
12.790091261990
 
4.2%
-31.095176011990
 
4.2%
13.259452411990
 
4.2%
21.942633641990
 
4.2%
13.024771841990
 
4.2%
-30.391134291990
 
4.2%
-21.003911341990
 
4.2%
Other values (14)27860
58.3%
ValueCountFrequency (%)
-31.095176011990
4.2%
-30.860495441990
4.2%
-30.625814861990
4.2%
-30.391134291990
4.2%
-24.99348111990
4.2%
-24.758800521990
4.2%
-24.524119951990
4.2%
-24.289439371990
4.2%
-21.238591921990
4.2%
-21.003911341990
4.2%
ValueCountFrequency (%)
24.05475881990
4.2%
23.820078231990
4.2%
23.585397651990
4.2%
23.350717081990
4.2%
22.177314211990
4.2%
21.942633641990
4.2%
21.707953061990
4.2%
21.473272491990
4.2%
13.494132991990
4.2%
13.259452411990
4.2%

lon
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct35
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean269.2708333
Minimum229.0625
Maximum354.375
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:48.359148image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum229.0625
5-th percentile229.375
Q1241.875
median253.125
Q3277.1875
95-th percentile354.0625
Maximum354.375
Range125.3125
Interquartile range (IQR)35.3125

Descriptive statistics

Standard deviation41.04659064
Coefficient of variation (CV)0.1524360813
Kurtosis0.1842010681
Mean269.2708333
Median Absolute Deviation (MAD)22.8125
Skewness1.226823569
Sum12860375
Variance1684.822603
MonotonicityNot monotonic
2021-10-19T16:02:48.439559image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
242.18751592
 
3.3%
241.8751592
 
3.3%
252.51592
 
3.3%
353.43751592
 
3.3%
253.751592
 
3.3%
353.1251592
 
3.3%
353.751592
 
3.3%
2301592
 
3.3%
253.43751592
 
3.3%
354.3751592
 
3.3%
Other values (25)31840
66.7%
ValueCountFrequency (%)
229.06251592
3.3%
229.3751592
3.3%
229.68751592
3.3%
2301592
3.3%
230.31251592
3.3%
241.251592
3.3%
241.56251592
3.3%
241.8751592
3.3%
242.18751592
3.3%
242.51592
3.3%
ValueCountFrequency (%)
354.3751592
3.3%
354.06251592
3.3%
353.751592
3.3%
353.43751592
3.3%
353.1251592
3.3%
277.81251592
3.3%
277.51592
3.3%
277.18751592
3.3%
276.8751592
3.3%
276.56251592
3.3%

TMQ
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct22540
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.83567924
Minimum6.960678577
Maximum80.64135742
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:48.523038image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.960678577
5-th percentile14.71919823
Q124.03308296
median34.89657402
Q344.72710133
95-th percentile55.55688438
Maximum80.64135742
Range73.68067884
Interquartile range (IQR)20.69401837

Descriptive statistics

Standard deviation12.86955225
Coefficient of variation (CV)0.3694359499
Kurtosis-0.8921152468
Mean34.83567924
Median Absolute Deviation (MAD)10.33487129
Skewness0.05657486896
Sum1663752.04
Variance165.6253752
MonotonicityNot monotonic
2021-10-19T16:02:48.610223image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45.1634178212
 
< 0.1%
23.4667797112
 
< 0.1%
23.7013835912
 
< 0.1%
50.5480079712
 
< 0.1%
44.5151710512
 
< 0.1%
44.9030227712
 
< 0.1%
44.2259826712
 
< 0.1%
46.5052375812
 
< 0.1%
22.6298980712
 
< 0.1%
43.8895988512
 
< 0.1%
Other values (22530)47640
99.7%
ValueCountFrequency (%)
6.9606785774
< 0.1%
6.9737534524
< 0.1%
7.0097923284
< 0.1%
7.0157585144
< 0.1%
7.0191140174
< 0.1%
7.0719604494
< 0.1%
7.1614542014
< 0.1%
7.1759557724
< 0.1%
7.215767864
< 0.1%
7.3604402544
< 0.1%
ValueCountFrequency (%)
80.641357422
< 0.1%
78.909431462
< 0.1%
76.891204832
< 0.1%
76.77136232
< 0.1%
75.315834052
< 0.1%
74.268501282
< 0.1%
73.321968081
< 0.1%
71.499107362
< 0.1%
70.700141912
< 0.1%
70.606010442
< 0.1%

U850
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct22555
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.6202928004
Minimum-58.80522919
Maximum32.27734375
Zeros0
Zeros (%)0.0%
Negative28167
Negative (%)59.0%
Memory size373.2 KiB
2021-10-19T16:02:48.701513image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-58.80522919
5-th percentile-9.926419973
Q1-5.507041931
median-1.671802103
Q33.621787548
95-th percentile11.34012828
Maximum32.27734375
Range91.08257294
Interquartile range (IQR)9.128829479

Descriptive statistics

Standard deviation6.84730737
Coefficient of variation (CV)-11.03883096
Kurtosis1.322524691
Mean-0.6202928004
Median Absolute Deviation (MAD)4.398510873
Skewness0.59574113
Sum-29625.18415
Variance46.88561822
MonotonicityNot monotonic
2021-10-19T16:02:48.785410image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-9.28049755112
 
< 0.1%
8.19553279912
 
< 0.1%
-0.91788989312
 
< 0.1%
-7.90840196612
 
< 0.1%
-2.53519463512
 
< 0.1%
0.45115444112
 
< 0.1%
-9.1665229812
 
< 0.1%
7.83004474612
 
< 0.1%
7.72073936512
 
< 0.1%
7.45763158812
 
< 0.1%
Other values (22545)47640
99.7%
ValueCountFrequency (%)
-58.805229192
< 0.1%
-45.996341712
< 0.1%
-42.340290072
< 0.1%
-37.68472292
< 0.1%
-33.228141782
< 0.1%
-30.951225282
< 0.1%
-28.039558412
< 0.1%
-26.99584772
< 0.1%
-25.973718642
< 0.1%
-25.6425192
< 0.1%
ValueCountFrequency (%)
32.277343754
< 0.1%
32.065555574
< 0.1%
32.04383854
< 0.1%
32.025901794
< 0.1%
31.9542164
< 0.1%
31.626560214
< 0.1%
31.57729344
< 0.1%
31.565311434
< 0.1%
31.336782464
< 0.1%
31.260623934
< 0.1%

V850
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct22558
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01040468742
Minimum-26.21690559
Maximum58.06024551
Zeros0
Zeros (%)0.0%
Negative22959
Negative (%)48.1%
Memory size373.2 KiB
2021-10-19T16:02:48.869968image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-26.21690559
5-th percentile-6.863656521
Q1-2.30753541
median0.1571722325
Q32.34177947
95-th percentile6.42058959
Maximum58.06024551
Range84.2771511
Interquartile range (IQR)4.64931488

Descriptive statistics

Standard deviation4.332385262
Coefficient of variation (CV)416.3878344
Kurtosis8.253969421
Mean0.01040468742
Median Absolute Deviation (MAD)2.305080623
Skewness0.4901940357
Sum496.9278711
Variance18.76956206
MonotonicityNot monotonic
2021-10-19T16:02:48.949646image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.45649674513
 
< 0.1%
2.08598852212
 
< 0.1%
-6.52576971112
 
< 0.1%
-1.7189475312
 
< 0.1%
2.21470665912
 
< 0.1%
1.74520814412
 
< 0.1%
2.26530814212
 
< 0.1%
-1.54265630212
 
< 0.1%
-5.24851751312
 
< 0.1%
-0.29796811912
 
< 0.1%
Other values (22548)47639
99.7%
ValueCountFrequency (%)
-26.216905591
 
< 0.1%
-24.260339741
 
< 0.1%
-22.856197369
< 0.1%
-22.360260011
 
< 0.1%
-20.975997922
 
< 0.1%
-20.784065252
 
< 0.1%
-20.668685912
 
< 0.1%
-20.510583881
 
< 0.1%
-20.449249272
 
< 0.1%
-20.344446182
 
< 0.1%
ValueCountFrequency (%)
58.060245512
< 0.1%
57.1957552
< 0.1%
51.691051482
< 0.1%
44.481063842
< 0.1%
42.691631322
< 0.1%
42.142948152
< 0.1%
40.456748961
< 0.1%
40.012062071
< 0.1%
37.895015721
< 0.1%
37.802089692
< 0.1%

UBOT
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct22556
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.152124212
Minimum-58.26047516
Maximum30.21538734
Zeros0
Zeros (%)0.0%
Negative31669
Negative (%)66.3%
Memory size373.2 KiB
2021-10-19T16:02:49.033181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-58.26047516
5-th percentile-10.7093401
Q1-6.589128137
median-2.687852859
Q31.720814586
95-th percentile8.074259758
Maximum30.21538734
Range88.4758625
Interquartile range (IQR)8.309942723

Descriptive statistics

Standard deviation6.043284278
Coefficient of variation (CV)-2.808055522
Kurtosis1.418276311
Mean-2.152124212
Median Absolute Deviation (MAD)4.123464227
Skewness0.3741793121
Sum-102785.4524
Variance36.52128487
MonotonicityNot monotonic
2021-10-19T16:02:49.114098image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.72645115912
 
< 0.1%
-5.37012004912
 
< 0.1%
-0.48655891412
 
< 0.1%
-5.1749973312
 
< 0.1%
-7.60008668912
 
< 0.1%
-9.85020065312
 
< 0.1%
-0.6099524512
 
< 0.1%
-1.16564238112
 
< 0.1%
2.03775858912
 
< 0.1%
-4.7815847412
 
< 0.1%
Other values (22546)47640
99.7%
ValueCountFrequency (%)
-58.260475162
< 0.1%
-56.400234222
< 0.1%
-48.993064882
< 0.1%
-46.387168882
< 0.1%
-41.747562412
< 0.1%
-38.990676882
< 0.1%
-34.880195622
< 0.1%
-32.662784582
< 0.1%
-29.441940312
< 0.1%
-26.650838852
< 0.1%
ValueCountFrequency (%)
30.215387349
< 0.1%
30.041025169
< 0.1%
27.409748081
 
< 0.1%
25.678833019
< 0.1%
25.676321031
 
< 0.1%
25.647541051
 
< 0.1%
24.881940849
< 0.1%
24.554573069
< 0.1%
24.040193561
 
< 0.1%
23.15342141
 
< 0.1%

VBOT
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct22555
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.7594554537
Minimum-20.76045227
Maximum31.10628319
Zeros0
Zeros (%)0.0%
Negative27477
Negative (%)57.5%
Memory size373.2 KiB
2021-10-19T16:02:49.197284image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-20.76045227
5-th percentile-7.972915173
Q1-3.800055504
median-0.774992228
Q32.072185516
95-th percentile7.348595953
Maximum31.10628319
Range51.86673546
Interquartile range (IQR)5.87224102

Descriptive statistics

Standard deviation4.761139356
Coefficient of variation (CV)-6.269148945
Kurtosis1.070025514
Mean-0.7594554537
Median Absolute Deviation (MAD)2.938357115
Skewness0.09944131666
Sum-36271.59247
Variance22.66844797
MonotonicityNot monotonic
2021-10-19T16:02:49.283424image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.55380439812
 
< 0.1%
2.58981609312
 
< 0.1%
-0.1897546812
 
< 0.1%
-4.12211990412
 
< 0.1%
-0.08244536812
 
< 0.1%
2.78530931512
 
< 0.1%
2.21136832212
 
< 0.1%
0.19429118912
 
< 0.1%
2.48682713512
 
< 0.1%
2.02155876212
 
< 0.1%
Other values (22545)47640
99.7%
ValueCountFrequency (%)
-20.760452274
< 0.1%
-20.588073734
< 0.1%
-20.517736434
< 0.1%
-20.413068774
< 0.1%
-20.21537594
< 0.1%
-20.215196614
< 0.1%
-19.808759694
< 0.1%
-19.804992684
< 0.1%
-19.7026314
< 0.1%
-19.378103264
< 0.1%
ValueCountFrequency (%)
31.106283191
< 0.1%
29.72228051
< 0.1%
29.09798051
< 0.1%
28.453311921
< 0.1%
27.738056181
< 0.1%
26.737993241
< 0.1%
26.484743122
< 0.1%
25.953285222
< 0.1%
25.847339631
< 0.1%
24.388355262
< 0.1%

QREFHT
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct22533
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01437782205
Minimum0.004363584
Maximum0.022366185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:49.367921image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.004363584
5-th percentile0.007883972
Q10.011245365
median0.0145663525
Q30.017986557
95-th percentile0.02004644135
Maximum0.022366185
Range0.018002601
Interquartile range (IQR)0.006741192

Descriptive statistics

Standard deviation0.003969208683
Coefficient of variation (CV)0.2760646689
Kurtosis-1.019449112
Mean0.01437782205
Median Absolute Deviation (MAD)0.0033695055
Skewness-0.1902334219
Sum686.684781
Variance1.575461757 × 10-5
MonotonicityNot monotonic
2021-10-19T16:02:49.455402image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01910406212
 
< 0.1%
0.01371750912
 
< 0.1%
0.01804617612
 
< 0.1%
0.01836095212
 
< 0.1%
0.01122475312
 
< 0.1%
0.01409651412
 
< 0.1%
0.01352011312
 
< 0.1%
0.01460298412
 
< 0.1%
0.00890974612
 
< 0.1%
0.01801692912
 
< 0.1%
Other values (22523)47640
99.7%
ValueCountFrequency (%)
0.0043635841
< 0.1%
0.0044000071
< 0.1%
0.0044431041
< 0.1%
0.0044586121
< 0.1%
0.0045344691
< 0.1%
0.0045819231
< 0.1%
0.004625951
< 0.1%
0.0047186881
< 0.1%
0.0048067871
< 0.1%
0.004831181
< 0.1%
ValueCountFrequency (%)
0.0223661852
< 0.1%
0.0223284982
< 0.1%
0.0223211932
< 0.1%
0.0222909392
< 0.1%
0.0222877192
< 0.1%
0.0222843052
< 0.1%
0.0222724082
< 0.1%
0.0222626652
< 0.1%
0.0222485722
< 0.1%
0.0222452122
< 0.1%

PS
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct21520
Distinct (%)45.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101554.0515
Minimum96611.60156
Maximum103996.9531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:49.546481image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum96611.60156
5-th percentile100794.7621
Q1101152.1172
median101527.957
Q3101887.4766
95-th percentile102478.6477
Maximum103996.9531
Range7385.35154
Interquartile range (IQR)735.3594

Descriptive statistics

Standard deviation545.8635555
Coefficient of variation (CV)0.005375103674
Kurtosis1.612882194
Mean101554.0515
Median Absolute Deviation (MAD)369.52345
Skewness0.2623202251
Sum4850221501
Variance297967.0212
MonotonicityNot monotonic
2021-10-19T16:02:49.630966image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10106518
 
< 0.1%
101044.820317
 
< 0.1%
101403.757817
 
< 0.1%
100825.476614
 
< 0.1%
101949.867213
 
< 0.1%
100846.242213
 
< 0.1%
100987.796913
 
< 0.1%
101149.804713
 
< 0.1%
100831.773412
 
< 0.1%
101934.664112
 
< 0.1%
Other values (21510)47618
99.7%
ValueCountFrequency (%)
96611.601562
 
< 0.1%
97497.796882
 
< 0.1%
97758.070312
 
< 0.1%
98168.554692
 
< 0.1%
98599.679692
 
< 0.1%
98739.554699
< 0.1%
98841.56252
 
< 0.1%
99125.140631
 
< 0.1%
99149.023441
 
< 0.1%
99275.851562
 
< 0.1%
ValueCountFrequency (%)
103996.95316
< 0.1%
103994.48446
< 0.1%
103990.83596
< 0.1%
103985.97666
< 0.1%
103979.40636
< 0.1%
103965.28136
< 0.1%
103962.86726
< 0.1%
103958.46096
< 0.1%
103956.35166
< 0.1%
103952.67196
< 0.1%

PSL
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct21537
Distinct (%)45.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101556.3416
Minimum96611.60156
Maximum103996.9531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:49.721161image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum96611.60156
5-th percentile100797.5078
Q1101157.6328
median101531.25
Q3101888.9336
95-th percentile102478.6477
Maximum103996.9531
Range7385.35154
Interquartile range (IQR)731.3008

Descriptive statistics

Standard deviation544.8552807
Coefficient of variation (CV)0.005365054234
Kurtosis1.629806163
Mean101556.3416
Median Absolute Deviation (MAD)369.8242
Skewness0.2584526289
Sum4850330877
Variance296867.2769
MonotonicityNot monotonic
2021-10-19T16:02:49.806228image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10106518
 
< 0.1%
101044.820317
 
< 0.1%
101778.031315
 
< 0.1%
101838.882815
 
< 0.1%
101159.585914
 
< 0.1%
101465.093814
 
< 0.1%
101949.867213
 
< 0.1%
101390.492213
 
< 0.1%
101170.148412
 
< 0.1%
100844.109412
 
< 0.1%
Other values (21527)47617
99.7%
ValueCountFrequency (%)
96611.601562
 
< 0.1%
97498.906252
 
< 0.1%
97758.109382
 
< 0.1%
98175.43752
 
< 0.1%
98599.752
 
< 0.1%
98739.554699
< 0.1%
98852.132812
 
< 0.1%
99125.140631
 
< 0.1%
99149.023441
 
< 0.1%
99275.890632
 
< 0.1%
ValueCountFrequency (%)
103996.95316
< 0.1%
103994.48446
< 0.1%
103990.83596
< 0.1%
103985.97666
< 0.1%
103979.40636
< 0.1%
103965.28136
< 0.1%
103962.86726
< 0.1%
103958.46096
< 0.1%
103956.35166
< 0.1%
103952.67196
< 0.1%

T200
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct22068
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean216.8944601
Minimum208.8242493
Maximum229.1728973
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:49.897659image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum208.8242493
5-th percentile212.7711357
Q1215.504303
median217.1624374
Q3218.430748
95-th percentile220.1703949
Maximum229.1728973
Range20.348648
Interquartile range (IQR)2.926445

Descriptive statistics

Standard deviation2.307293768
Coefficient of variation (CV)0.010637864
Kurtosis0.7776898554
Mean216.8944601
Median Absolute Deviation (MAD)1.44298555
Skewness-0.3448448429
Sum10358879.41
Variance5.323604531
MonotonicityNot monotonic
2021-10-19T16:02:49.988703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
217.608734113
 
< 0.1%
218.125839213
 
< 0.1%
217.44787612
 
< 0.1%
215.585052512
 
< 0.1%
215.607818612
 
< 0.1%
217.81208812
 
< 0.1%
215.587509212
 
< 0.1%
217.25860612
 
< 0.1%
217.550567612
 
< 0.1%
215.610916112
 
< 0.1%
Other values (22058)47638
99.7%
ValueCountFrequency (%)
208.82424932
< 0.1%
208.83410642
< 0.1%
208.83531192
< 0.1%
208.85217292
< 0.1%
208.85504152
< 0.1%
208.85675052
< 0.1%
208.8752
< 0.1%
208.88479612
< 0.1%
208.8962862
< 0.1%
208.9396822
< 0.1%
ValueCountFrequency (%)
229.17289732
< 0.1%
227.11923222
< 0.1%
226.76000984
< 0.1%
226.69656374
< 0.1%
226.69265754
< 0.1%
226.56159974
< 0.1%
226.49525454
< 0.1%
226.48359684
< 0.1%
226.47718814
< 0.1%
226.36842354
< 0.1%

T500
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct21789
Distinct (%)45.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean264.3758061
Minimum249.1460114
Maximum273.5808105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:50.080360image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum249.1460114
5-th percentile256.6629532
Q1262.9100647
median265.2451172
Q3266.8773498
95-th percentile268.2765503
Maximum273.5808105
Range24.4347991
Interquartile range (IQR)3.967285125

Descriptive statistics

Standard deviation3.507889067
Coefficient of variation (CV)0.01326857067
Kurtosis1.444957738
Mean264.3758061
Median Absolute Deviation (MAD)1.8566894
Skewness-1.269383537
Sum12626588.5
Variance12.30528571
MonotonicityNot monotonic
2021-10-19T16:02:50.167374image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
267.26132218
 
< 0.1%
262.503601114
 
< 0.1%
267.200805714
 
< 0.1%
267.171112114
 
< 0.1%
265.800964414
 
< 0.1%
267.148071314
 
< 0.1%
267.41839613
 
< 0.1%
263.308929413
 
< 0.1%
265.56945813
 
< 0.1%
265.69622813
 
< 0.1%
Other values (21779)47620
99.7%
ValueCountFrequency (%)
249.14601141
< 0.1%
249.3751
< 0.1%
249.59210211
< 0.1%
249.63696291
< 0.1%
249.8007051
< 0.1%
249.83618161
< 0.1%
249.89964292
< 0.1%
249.90156562
< 0.1%
249.90574652
< 0.1%
249.92369082
< 0.1%
ValueCountFrequency (%)
273.58081052
 
< 0.1%
273.04556272
 
< 0.1%
272.24105831
 
< 0.1%
272.15228272
 
< 0.1%
272.14736941
 
< 0.1%
272.10958869
< 0.1%
271.97988892
 
< 0.1%
271.94149782
 
< 0.1%
271.88726812
 
< 0.1%
271.41995242
 
< 0.1%

PRECT
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct6506
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.629729643 × 10-8
Minimum-4.4 × 10-23
Maximum1.44 × 10-5
Zeros1192
Zeros (%)2.5%
Negative53
Negative (%)0.1%
Memory size373.2 KiB
2021-10-19T16:02:50.254281image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-4.4 × 10-23
5-th percentile7.21 × 10-18
Q11.61 × 10-14
median5.28 × 10-9
Q33.12 × 10-8
95-th percentile2.01 × 10-7
Maximum1.44 × 10-5
Range1.44 × 10-5
Interquartile range (IQR)3.11999839 × 10-8

Descriptive statistics

Standard deviation2.385749753 × 10-7
Coefficient of variation (CV)5.153108145
Kurtosis1758.33619
Mean4.629729643 × 10-8
Median Absolute Deviation (MAD)5.279999618 × 10-9
Skewness35.72065413
Sum0.002211158878
Variance5.691801886 × 10-14
MonotonicityNot monotonic
2021-10-19T16:02:50.339415image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01192
 
2.5%
1.3 × 10-885
 
0.2%
1.16 × 10-882
 
0.2%
1.13 × 10-882
 
0.2%
1.1 × 10-880
 
0.2%
1.43 × 10-876
 
0.2%
1.06 × 10-876
 
0.2%
1.2 × 10-876
 
0.2%
1.02 × 10-776
 
0.2%
1.4 × 10-876
 
0.2%
Other values (6496)45859
96.0%
ValueCountFrequency (%)
-4.4 × 10-231
 
< 0.1%
-3.94 × 10-232
< 0.1%
-3.5 × 10-232
< 0.1%
-1.51 × 10-232
< 0.1%
-1.4 × 10-231
 
< 0.1%
-1.38 × 10-234
< 0.1%
-7.22 × 10-241
 
< 0.1%
-4.92 × 10-243
< 0.1%
-2.89 × 10-241
 
< 0.1%
-2.53 × 10-244
< 0.1%
ValueCountFrequency (%)
1.44 × 10-52
< 0.1%
1.41 × 10-51
< 0.1%
1.39 × 10-52
< 0.1%
1.13 × 10-51
< 0.1%
9.91 × 10-61
< 0.1%
9.89 × 10-62
< 0.1%
9.27 × 10-62
< 0.1%
7.16 × 10-62
< 0.1%
6.75 × 10-61
< 0.1%
6.51 × 10-62
< 0.1%

TS
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct9827
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean298.3094671
Minimum289.3307495
Maximum303.869812
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:50.426173image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum289.3307495
5-th percentile290.756073
Q1295.8606873
median298.6851807
Q3301.7601013
95-th percentile302.973053
Maximum303.869812
Range14.5390625
Interquartile range (IQR)5.899414

Descriptive statistics

Standard deviation3.794154724
Coefficient of variation (CV)0.01271885455
Kurtosis-0.6509486825
Mean298.3094671
Median Absolute Deviation (MAD)2.9872131
Skewness-0.5920260096
Sum14247260.15
Variance14.39561007
MonotonicityNot monotonic
2021-10-19T16:02:50.510133image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
302.7839355108
 
0.2%
302.099975681
 
0.2%
300.934570381
 
0.2%
299.067779581
 
0.2%
290.75607372
 
0.2%
295.819488572
 
0.2%
295.665954672
 
0.2%
302.660034257
 
0.1%
297.874389654
 
0.1%
297.999145554
 
0.1%
Other values (9817)47028
98.5%
ValueCountFrequency (%)
289.33074953
 
< 0.1%
289.33569346
< 0.1%
289.35015872
 
< 0.1%
289.35485844
< 0.1%
289.39819343
 
< 0.1%
289.4019474
< 0.1%
289.40591438
< 0.1%
289.41247562
 
< 0.1%
289.42245481
 
< 0.1%
289.42248542
 
< 0.1%
ValueCountFrequency (%)
303.86981212
 
< 0.1%
303.81430054
 
< 0.1%
303.81414796
 
< 0.1%
303.80990618
< 0.1%
303.8081364
 
< 0.1%
303.78881846
 
< 0.1%
303.78646856
 
< 0.1%
303.78585822
 
< 0.1%
303.76013182
 
< 0.1%
303.738494936
0.1%

TREFHT
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct21892
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean296.8927182
Minimum285.4266663
Maximum304.3641968
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:50.600908image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum285.4266663
5-th percentile289.3610687
Q1294.2211532
median297.3013306
Q3300.47406
95-th percentile301.9136719
Maximum304.3641968
Range18.9375305
Interquartile range (IQR)6.2529068

Descriptive statistics

Standard deviation4.021796553
Coefficient of variation (CV)0.01354629571
Kurtosis-0.6599202761
Mean296.8927182
Median Absolute Deviation (MAD)3.1482239
Skewness-0.5493110957
Sum14179596.22
Variance16.17484751
MonotonicityNot monotonic
2021-10-19T16:02:50.689020image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
295.113189714
 
< 0.1%
301.723693814
 
< 0.1%
297.415618914
 
< 0.1%
300.444641114
 
< 0.1%
301.412963913
 
< 0.1%
301.655853313
 
< 0.1%
301.700958313
 
< 0.1%
297.807708713
 
< 0.1%
294.478576713
 
< 0.1%
301.515380913
 
< 0.1%
Other values (21882)47626
99.7%
ValueCountFrequency (%)
285.42666632
< 0.1%
285.53146362
< 0.1%
285.53332522
< 0.1%
285.57876592
< 0.1%
285.61688232
< 0.1%
285.72692872
< 0.1%
285.7438662
< 0.1%
285.75820922
< 0.1%
285.7603762
< 0.1%
285.76940922
< 0.1%
ValueCountFrequency (%)
304.36419684
< 0.1%
304.20736694
< 0.1%
304.20697024
< 0.1%
304.17120364
< 0.1%
304.1440434
< 0.1%
304.13952644
< 0.1%
304.0061344
< 0.1%
303.99639894
< 0.1%
303.97192381
 
< 0.1%
303.93420411
 
< 0.1%

Z1000
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct22535
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.5228818
Minimum63.33520508
Maximum328.1236877
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:50.778247image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum63.33520508
5-th percentile70.62041474
Q1101.8364868
median133.7729797
Q3162.6830597
95-th percentile209.1255181
Maximum328.1236877
Range264.7884826
Interquartile range (IQR)60.8465729

Descriptive statistics

Standard deviation42.51809578
Coefficient of variation (CV)0.3137337046
Kurtosis0.4825892466
Mean135.5228818
Median Absolute Deviation (MAD)30.70470045
Skewness0.5595417999
Sum6472572.837
Variance1807.788469
MonotonicityNot monotonic
2021-10-19T16:02:50.861851image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
166.80725112
 
< 0.1%
75.4570922912
 
< 0.1%
224.989669812
 
< 0.1%
164.443023712
 
< 0.1%
102.927764912
 
< 0.1%
103.98042312
 
< 0.1%
103.311935412
 
< 0.1%
167.70613112
 
< 0.1%
102.118583712
 
< 0.1%
168.554565412
 
< 0.1%
Other values (22525)47640
99.7%
ValueCountFrequency (%)
63.335205082
< 0.1%
63.376960752
< 0.1%
63.394424442
< 0.1%
63.410236362
< 0.1%
63.410446172
< 0.1%
63.438934332
< 0.1%
63.446720122
< 0.1%
63.457988742
< 0.1%
63.4662592
< 0.1%
63.467864992
< 0.1%
ValueCountFrequency (%)
328.12368776
< 0.1%
327.94989016
< 0.1%
327.67675786
< 0.1%
327.32745366
< 0.1%
326.89111336
< 0.1%
325.79733286
< 0.1%
325.61941536
< 0.1%
325.34436046
< 0.1%
325.19656376
< 0.1%
324.96038826
< 0.1%

Z200
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct21880
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12291.61773
Minimum11718.24902
Maximum12511.0332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:50.946578image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum11718.24902
5-th percentile12013.43804
Q112229.98242
median12321.94629
Q312391.46094
95-th percentile12440.08203
Maximum12511.0332
Range792.78418
Interquartile range (IQR)161.47852

Descriptive statistics

Standard deviation130.9269218
Coefficient of variation (CV)0.01065172418
Kurtosis1.195862407
Mean12291.61773
Median Absolute Deviation (MAD)78.0625
Skewness-1.187312195
Sum587047662.6
Variance17141.85884
MonotonicityNot monotonic
2021-10-19T16:02:51.031647image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12347.0419915
 
< 0.1%
12401.8017615
 
< 0.1%
12277.466815
 
< 0.1%
12125.3984415
 
< 0.1%
12343.5966815
 
< 0.1%
12409.5488314
 
< 0.1%
12402.029314
 
< 0.1%
12254.841813
 
< 0.1%
12379.0947312
 
< 0.1%
12255.8828112
 
< 0.1%
Other values (21870)47620
99.7%
ValueCountFrequency (%)
11718.249021
< 0.1%
11723.48731
< 0.1%
11727.396481
< 0.1%
11728.550781
< 0.1%
11732.353521
< 0.1%
11733.717771
< 0.1%
11736.583011
< 0.1%
11737.162111
< 0.1%
11738.854491
< 0.1%
11741.315431
< 0.1%
ValueCountFrequency (%)
12511.03324
< 0.1%
12510.793954
< 0.1%
12510.705084
< 0.1%
12510.447274
< 0.1%
12509.960944
< 0.1%
12509.361334
< 0.1%
12508.943364
< 0.1%
12508.563484
< 0.1%
12508.426764
< 0.1%
12507.818364
< 0.1%

ZBOT
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct21964
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.37813712
Minimum62.43359375
Maximum67.13165283
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:51.118989image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum62.43359375
5-th percentile63.47643661
Q164.6577282
median65.47276306
Q366.32779694
95-th percentile66.69106522
Maximum67.13165283
Range4.69805908
Interquartile range (IQR)1.67006874

Descriptive statistics

Standard deviation1.041088621
Coefficient of variation (CV)0.01592410961
Kurtosis-0.7411904786
Mean65.37813712
Median Absolute Deviation (MAD)0.84510803
Skewness-0.499583058
Sum3122459.829
Variance1.083865517
MonotonicityNot monotonic
2021-10-19T16:02:51.204782image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.5153884921
 
< 0.1%
66.6276092516
 
< 0.1%
64.876426715
 
< 0.1%
65.4810562114
 
< 0.1%
65.9071197513
 
< 0.1%
65.4784851113
 
< 0.1%
66.5095367413
 
< 0.1%
66.618797313
 
< 0.1%
65.4856262213
 
< 0.1%
65.4842605613
 
< 0.1%
Other values (21954)47616
99.7%
ValueCountFrequency (%)
62.433593752
< 0.1%
62.451129912
< 0.1%
62.454742432
< 0.1%
62.457977292
< 0.1%
62.478816992
< 0.1%
62.485363012
< 0.1%
62.493045812
< 0.1%
62.498512272
< 0.1%
62.507122042
< 0.1%
62.508766172
< 0.1%
ValueCountFrequency (%)
67.131652831
 
< 0.1%
67.125434881
 
< 0.1%
67.117370611
 
< 0.1%
67.103179934
< 0.1%
67.068748471
 
< 0.1%
67.067466741
 
< 0.1%
67.066719064
< 0.1%
67.066024781
 
< 0.1%
67.055572514
< 0.1%
67.055282591
 
< 0.1%

time
Real number (ℝ≥0)

Distinct188
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20023933.29
Minimum19960609
Maximum20101029
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size373.2 KiB
2021-10-19T16:02:51.291393image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19960609
5-th percentile19970814
Q120000906
median20011207
Q320040819
95-th percentile20100830
Maximum20101029
Range140420
Interquartile range (IQR)39913

Descriptive statistics

Standard deviation36588.71087
Coefficient of variation (CV)0.00182724894
Kurtosis-0.30707828
Mean20023933.29
Median Absolute Deviation (MAD)10589
Skewness0.6861266075
Sum9.563430538 × 1011
Variance1338733763
MonotonicityNot monotonic
2021-10-19T16:02:51.376646image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200009061440
 
3.0%
200112071080
 
2.3%
200206221080
 
2.3%
200211171080
 
2.3%
20010722720
 
1.5%
20010303720
 
1.5%
20010712720
 
1.5%
20001220720
 
1.5%
20000417720
 
1.5%
20011029600
 
1.3%
Other values (178)38880
81.4%
ValueCountFrequency (%)
19960609120
 
0.3%
19960711120
 
0.3%
19960718360
0.8%
19960901240
0.5%
19960912120
 
0.3%
19960926240
0.5%
19961003240
0.5%
19970601120
 
0.3%
19970602120
 
0.3%
19970605120
 
0.3%
ValueCountFrequency (%)
20101029120
 
0.3%
20101022240
0.5%
20101019240
0.5%
20101010360
0.8%
20101009240
0.5%
20100925480
1.0%
20100909240
0.5%
20100830480
1.0%
20100705240
0.5%
20100702120
 
0.3%

LABELS
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size373.2 KiB
0
37535 
2
8223 
1
 
2002

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
037535
78.6%
28223
 
17.2%
12002
 
4.2%

Length

2021-10-19T16:02:51.458428image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-19T16:02:51.503002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
037535
78.6%
28223
 
17.2%
12002
 
4.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Interactions

2021-10-19T16:02:45.514915image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:13.635095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:15.245718image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:17.069750image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:18.671654image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:20.329624image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:21.940884image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:23.512728image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:25.360787image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:26.958997image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:28.650814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:30.315257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:31.982790image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:33.914747image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:35.482730image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:37.125590image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:38.772520image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:40.713841image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:42.269318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:43.952802image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:45.597469image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:13.721878image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:15.321668image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:17.147865image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:18.750495image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:20.415860image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:22.019609image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:23.587276image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:25.439980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:27.043660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:28.732091image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:30.396201image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:32.064426image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:33.989822image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:35.567671image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:37.204178image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:38.856471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:40.789779image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:42.351142image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:44.028146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:45.679340image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:13.800961image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:15.396548image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:17.225569image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:18.829244image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:20.499498image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:22.095883image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:23.673319image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:25.519252image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:27.129124image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:28.812385image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:30.475929image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:32.146071image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:34.068010image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:35.648589image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:37.284072image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:38.938365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:40.864158image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:42.431672image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:44.110151image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:45.763581image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:13.880089image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:15.475222image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:17.304775image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:18.909765image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:20.578815image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:22.174202image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:23.755931image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:25.600462image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:27.219873image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:28.895456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:30.559139image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:32.476517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:34.147887image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:35.729961image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:37.365361image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:39.022228image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:40.941709image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:42.516952image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:44.190886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:45.848784image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:13.962744image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:15.555798image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:17.386207image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:18.992133image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:20.661439image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:22.252378image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:23.839517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:25.680606image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:27.307009image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:28.979525image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:30.644047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:32.561656image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:34.228264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:35.813047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:37.447269image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:39.108260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:41.022113image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:42.602817image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:44.269782image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:45.927748image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:14.037870image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:15.630247image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:17.461896image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:19.069379image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:20.735805image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:22.324917image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:23.916538image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
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2021-10-19T16:02:28.226560image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:29.888766image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:31.558711image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:33.487528image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:35.082946image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:36.710137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:38.341935image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:40.283785image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:41.873152image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:43.526658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:45.120485image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:46.865514image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:14.925650image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:16.754228image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:18.349719image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:19.971190image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:21.613005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:23.196391image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:25.046835image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:26.642439image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:28.315928image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:29.977335image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:31.647318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:33.576985image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:35.166371image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:36.796790image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:38.428645image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:40.373908image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:41.957427image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:43.616150image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:45.202905image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:46.945058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:15.001295image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:16.827723image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:18.424595image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:20.049149image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:21.689503image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:23.271244image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:25.119728image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:26.716616image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:28.395101image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:30.056532image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:31.726085image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:33.656409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:35.239031image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:36.873883image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:38.506790image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:40.453627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:42.029749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:43.695188image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:45.276721image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:47.033984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:15.086149image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:16.911166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:18.509710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:20.136634image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:21.776240image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:23.354291image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:25.201666image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:26.799515image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:28.482390image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:30.146451image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:31.813703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:33.744439image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:35.321085image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:36.960531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:38.596022image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:40.542560image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:42.111365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:43.782995image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:45.359041image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:47.113857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:15.161364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:16.986218image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:18.586376image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:20.216801image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:21.854029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:23.428493image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:25.275573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:26.874540image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:28.562928image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:30.226597image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:31.894278image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:33.825534image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:35.396924image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:37.038036image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:38.681173image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:40.624454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:42.185581image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:43.863261image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-19T16:02:45.433591image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2021-10-19T16:02:51.566668image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-10-19T16:02:51.705682image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-10-19T16:02:51.843549image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-10-19T16:02:51.981573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2021-10-19T16:02:47.278974image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2021-10-19T16:02:47.537566image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

S.NolatlonTMQU850V850UBOTVBOTQREFHTPSPSLT200T500PRECTTSTREFHTZ1000Z200ZBOTtimeLABELS
00-24.758801242.187516.019615-4.3916964.777769-6.3882227.7253200.010277102326.2344102326.2344221.594223261.8232126.660000e-09295.622253293.301514197.69862412234.7880964.372635200308040
1123.820078277.812547.8020368.6236529.3085664.5961059.9382860.018531100803.1094100803.1094220.343719269.1067203.670000e-16302.496826302.65408371.57151812463.9726666.834389200710061
2223.820078276.875011.556691-2.483993-6.009627-3.503036-5.9219630.007468101885.3906101885.3906215.933487259.6107180.000000e+00299.854919293.339996160.41424612099.3613364.209663200203310
3313.494133253.125053.1866300.150933-1.3194073.757741-2.1721200.018809100824.6328100824.6328218.457672267.3743299.800000e-08301.606934299.97345072.84061412379.2685566.243294200009060
44-24.524120241.250023.353998-7.467506-5.113565-9.545109-4.6912210.011672102553.8984102553.8984214.316605263.5754096.410000e-09295.819488295.101257218.44957012261.2265664.876427200009060
55-24.524120241.562543.42450310.390884-10.7374042.822728-11.2612130.014424101099.9375101099.9375215.881454264.0984195.650000e-08296.483215296.17718595.62209312237.6171965.247345200109192
66-24.993481242.187534.667477-1.8415433.9885391.7426896.6610320.013957101552.2656101552.2656213.257233264.0751953.570000e-09299.140747297.297180134.93403612242.4687565.431206200104250
7723.585398277.500051.990341-5.0573510.096988-7.096673-2.2934880.019915101255.5313101257.5938218.921753267.1797181.580000e-07302.065552300.926056111.31336212418.0966866.488510201010090
88-20.769231229.375032.008644-2.976694-4.964599-7.199704-3.8519140.013965101747.2266101747.2266217.324051264.9366451.240000e-08298.445404297.469147151.78125012283.6621165.483292200007240
9923.820078276.875047.643150-8.193987-0.7936532.222956-2.4835540.014301101641.0391101641.0391219.292892267.6572881.640000e-13302.688385301.619019144.73619112478.6181666.431099201007050

Last rows

S.NolatlonTMQU850V850UBOTVBOTQREFHTPSPSLT200T500PRECTTSTREFHTZ1000Z200ZBOTtimeLABELS
477504775013.494133253.750044.489532-2.837747-1.062834-3.629961-1.9916960.017999100848.6094100848.6094217.623413268.0184027.100000e-10302.839966301.31674275.25551612388.1093866.508980199706180
477514775124.054759276.875011.962342-2.036349-6.302435-2.934850-5.8105940.007507101893.3828101893.3828215.900635259.4648130.000000e+00299.182831293.266144161.09315512091.2255964.212830200203310
4775247752-24.758801242.187520.695261-5.7977992.092347-7.5111542.2997050.010850102363.1797102363.1797216.352249260.5073248.520000e-09295.336456293.732147201.26254312186.2207064.528435199710120
477534775322.177314244.687543.7954900.755373-1.2183500.056844-5.9674850.014017101054.1016101054.1016218.485275268.0667114.710000e-15298.962891297.14910991.87752512408.9472765.409462200009060
477544775413.024772253.437553.84825510.059551-0.7467919.8130801.1849480.019498100899.0000100899.0000218.412170266.8221442.430000e-07302.068481300.82037479.62416112387.6074266.427940200410030
4775547755-30.625815353.437514.6806133.1535184.250256-0.4069923.4805530.008333102109.4844102109.4844213.804184259.8462222.470000e-09291.791870290.141663177.67732212058.1601663.678669200011062
4775647756-24.993481242.187529.5405859.181329-0.3698057.125068-5.4664690.013645101734.2813101734.2813213.867416263.9963072.620000e-09296.322327296.220642150.10887112272.2578165.238327200107122
4775747757-30.625815353.437520.9911107.709649-6.2842923.702500-7.3595410.010529101800.8516101800.8516216.394852264.1925664.240000e-09290.757996290.736847152.66644312232.2695363.929737200110290
477584775823.585398276.562545.689816-3.0184480.280351-6.9381240.6810550.020653101641.2266101641.2266217.026199265.7789008.620000e-08302.751862301.542786145.25555412404.2929766.656548200207120
477594775924.054759276.875049.550251-2.582931-0.844238-6.318487-1.9861660.017553101374.0859101374.0859217.422790265.3355712.270000e-08301.325226300.146851121.04037512352.4853566.221062200810120